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Record W2464533948

Investigating the Relationship Between Climate Change and Tropical Parasitic Disease

2015· article· en· W2464533948 on OpenAlexaff
Russell Yanofsky

Bibliographic record

VenueGlobal Health: Annual Review · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClimate changeParasitic diseasePopulationLymphatic filariasisMalariaEffects of global warmingGeographyGlobal warmingEcologyDiseaseBiologyEnvironmental healthFilariasisImmunologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Background: The International Panel on Climate Change (IPCC) has concluded that Earth’s climate has changed considerably in the last century, in part due to human-related activity (1). Based on the IPCC 2007 Report, the average surface temperature increased approximately 0.74°C ± 0.18 °C over the twentieth century (1). The increased temperatures are linked to changes in other parameters of Earth’s climate system, such as the rising sea-level and increased yearly number of heavy rainfalls, extreme flooding, and droughts (1,2). Such changes in the Earth’s climate system are predicted to continue over the twenty-first century (1,2). Given that a population’s survival is largely dependent on the Earth’s climate, increasing attention has been placed on whether climate change has affected parasitic disease patterns. In principle, climate can affect parasitic diseases with respect to changes in reproduction, development, and the population dynamics of the parasite and the parasite host (3). However, the effects of climate change on parasitic disease over the last century remain controversial. It is important to understand the relationship between climate change and parasitic disease in order for the development of appropriate and effective policies in disease prevention. Objectives and Methodology: The objective of the current study was to investigate and review the relationship between climate change and various parasitic diseases, including malaria, Chagas disease, leishmaniasis, schistosomiasis, and lymphatic filariasis, considering the potential consequences for the human population as well. Thus, a literature review was performed using OVID as the main search engine to review the existing evidence.Results: A total of 43 observational studies were analyzed (15 malaria, 7 Chagas disease, 11 leishmaniasis, 5 schistosomiasis, and 5 lymphatic filariasis). In reviewing the existing literature, it was observed that the vectors and parasites of the tropical parasite diseases are influenced by local temperatures, rainfall, and other climate indices. While malaria and leishmaniasis were predominantly positively associated with temperature increases (4, 5), Chagas disease was negatively associated with increased temperatures (6). The effects of temperature on Schistosomiasis and lymphatic filariasis were less consistent, with both positive and negative associations observed. The dominant hypothesis to account for the differing associations observed between parasites and temperature change is one of an optimal growth habitat for a given parasite (3). That is, while temperature positively influences vector and parasite survival, extreme temperatures can be detrimental to currently endemic regions (3). In examining precipitation patterns, with the exception of lymphatic filariasis, for which a positive association was observed (7), the effects of precipitation were mixed for other parasitic diseases studied. The effects of precipitation on infectious disease appear to be very specific to the region, as increased rainfall can produce both positive and negative results for the vectors studied (3).Conclusion: The current study demonstrates that climate change plays a fundamental role in the survival of vectors and parasites, and the transmission of infectious disease. The results suggest that climate change has altered the geographical distribution of infectious disease, particularly in regions previously unsuitable for vector and parasitic survival. Future studies should seek to define how much of the burden of infectious disease can be attributed to climate change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.288
GPT teacher head0.442
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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